Neuron-Level Knowledge Attribution in Large Language Models

Understand

Identifying important neurons for final predictions is essential for understanding the mechanisms of large language models.

• Due to computational constraints, current attribution techniques struggle to operate at neuron level.
• In this paper, we propose a static method for pinpointing significant neurons.
• Compared to seven other methods, our approach demonstrates superior performance across three metrics.